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Plutonium oxide is loaded onto a truck for shipping. Adam Parkison/ORNL, U.S. Dept. of Energy

In June, ORNL hit a milestone not seen in more than three decades: producing a production-quality amount of plutonium-238

The DEMAND single crystal diffractometer at the High Flux Isotope Reactor, or HFIR, is the latest neutron instrument at the Department of Energy’s Oak Ridge National Laboratory to be equipped with machine learning-assisted software, called ReTIA. Credit: Jeremy Rumsey/ORNL, U.S. Dept. of Energy

Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.

A new nanoscience study led by an ORNL quantum researcher takes a big-picture look at how scientists study materials at the smallest scales. Credit: Getty Images

A new nanoscience study led by a researcher at ORNL takes a big-picture look at how scientists study materials at the smallest scales.

ZEISS Head of Additive Manufacturing Technology Claus Hermannstaedter, left, and ORNL Interim Associate Laboratory Director for Energy Science and Technology Rick Raines sign a licensing agreement that allows ORNL’s machine-learning algorithm, Simurgh, to be used for rapid evaluations of 3D-printed components with industrial X-ray computed tomography, or CT. Using machine learning in CT scanning is expected to reduce the time and cost of inspections of 3D-printed parts by more than ten times.

A licensing agreement between the Department of Energy’s Oak Ridge National Laboratory and research partner ZEISS will enable industrial X-ray computed tomography, or CT, to perform rapid evaluations of 3D-printed components using ORNL’s machine

Diagram of faults affecting a conventional power system.

Researchers at the Department of Energy’s Oak Ridge National Laboratory are leading the way in understanding the effects of electrical faults in the modern U.S. power grid.

Cody Lloyd stands in front of images of historical nuclear field testing. The green and red dots are the machine learning algorithm recognizing features in the image. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Cody Lloyd became a nuclear engineer because of his interest in the Manhattan Project, the United States’ mission to advance nuclear science to end World War II. As a research associate in nuclear forensics at ORNL, Lloyd now teaches computers to interpret data from imagery of nuclear weapons tests from the 1950s and early 1960s, bringing his childhood fascination into his career

Jonathan Harter, a technical professional in ORNL’s Engineering Science and Technology Directorate, uses a robot and other automated methods to disassemble electric vehicle batteries for recycling or reuse in the electric grid. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

After being stabilized in an ambulance as he struggled to breathe, Jonathan Harter hit a low point. It was 2020, he was very sick with COVID-19, and his job as a lab technician at ORNL was ending along with his research funding.

Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

After completing a bachelor’s degree in biology, Toya Beiswenger didn’t intend to go into forensics. But almost two decades later, the nuclear security scientist at ORNL has found a way to appreciate the art of nuclear forensics.

Innovation Crossroads cohort 7

Seven entrepreneurs will embark on a two-year fellowship as the seventh cohort of Innovation Crossroads kicks off this month at ORNL. Representing a range of transformative energy technologies, Cohort 7 is a diverse class of innovators with promising new companies.

ORNL’s Fernanda Santos examines a soil sample at an NGEE Arctic field site in the Alaskan tundra in June 2022. Credit: Amy Breen, University of Alaska Fairbanks.

Wildfires are an ancient force shaping the environment, but they have grown in frequency, range and intensity in response to a changing climate. At ORNL, scientists are working on several fronts to better understand and predict these events and what they mean for the carbon cycle and biodiversity.